27 papers · ranked by Valyu relevance
Jing He, Qi-wei Kong, Ho-Chung Lui, Haitao Liu + 1 more
The definition of factor space and a unified optimization based classification model were developed for linear programming and supervised learning. Intelligent behaviour appeared in a decision process can be treated as a moving point y, the dynamic state observed and controlled by the agent, moving in a factor space…
Radoslaw Ryńca, Yasmin Ziaeian, Claudia Noemi González Brambila
In the past few decades, any type of organization, from factories to government organizations, the banking sector, or educational institutions concentrates on increasing profit margins. To achieve this, one of the key factors is to achieve maximum output with minimum resources (input). Therefore, having an optimal plan…
Oliver Serang, Jérémie Bourdon
Linear programming (LP) problems are commonly used in analysis and resource allocation, frequently surfacing as approximations to more difficult problems. Existing approaches to LP have been dominated by a small group of methods, and randomized algorithms have not enjoyed popularity in practice. This paper introduces a…
Catalina J. Villalba, Aurélio Ribeiro Leite de Oliveira
columns Authors: ['Catalina J. Villalba' 'Aurélio Ribeiro Leite de Oliveira'] The Interior-Point Methods are a class for solving linear programming problems that rely upon the solution of linear systems. At each iteration, it becomes important to determine how to solve these linear systems when the constraint matrix of…
Charalampos P. Triantafyllidis, Nikolaos Samaras, Sándor Szénási
This paper presents a new simplex-type algorithm for Linear Programming with the following two main characteristics: (i) the algorithm computes basic solutions which are neither primal or dual feasible, nor monotonically improving and (ii) the sequence of these basic solutions is connected with a sequence of…
Syed Inayatullah, Nasir Touheed, Muhammad Imtiaz, Cheng-Yi Xia
This paper proposes a streamlined form of simplex method which provides some great benefits over traditional simplex method. For instance, it does not need any kind of artificial variables or artificial constraints; it could start with any feasible or infeasible basis of an LP. This method follows the same pivoting…
Saeed Ketabchi, Hossein Moosaei, Hossein Sahleh, Mohammad Hedayati
In this study, calculations necessary to solve the large scale linear programming problems in two operating systems, Linux and Windows 7 (Win), are compared using two different methods. Relying on the interior-point methods, linear-programming interior point solvers (LIPSOL) software was used for the first method and…
Olesya Melnichenko, Venkat S. Malladi
In the field of genomics, bioinformatics pipelines play a crucial role in processing and analyzing vast biological datasets. These pipelines, consisting of interconnected tasks, can be optimized for efficiency and scalability by leveraging cloud platforms such as Microsoft Azure. The choice of compute resources…
Hendrik Schawe, Roman Bleim, Alexander K. Hartmann, Andrea Gambassi
Here we study linear programming applied to the random K-SAT problem, a fundamental problem in computational complexity. The K-SAT problem is to decide whether a Boolean formula with N variables and structured as a conjunction of M clauses, each being a disjunction of K variables or their negations is satisfiable or…
Deepesh Agarwal, Ryan T. Fellers, Bryan P. Early, Dan Lu + 6 more
Post-translational modifications (PTMs) at multiple sites can collectively influence protein function but the scope of such PTM coding has been challenging to determine. The number of potential combinatorial patterns of PTMs on a single molecule increases exponentially with the number of modification sites and a…
Jaan Übi, Evald Übi
In order to find a non-negative solution to a system of inequalities, the corresponding dual problem is composed, which has a suitable unity basic matrix. In such a formulation, the objective function is replaced by set of constraints based on that function. Additional constraints can be used for accelerating…
Ahmed Ibrahim, Attahiru Alfa
This paper is intended to serve as an overview of, and mostly a tutorial to illustrate, the optimization techniques used in several different key design aspects that have been considered in the literature of wireless sensor networks (WSNs). It targets the researchers who are new to the mathematical optimization tool…
Hao Cheng, Keyu Xu, Kuruvilla Joseph Abraham
Low-cost genome-wide single-nucleotide polymorphisms (SNPs) are routinely used in animal breeding programs. Compared to SNP arrays, the use of whole-genome sequence data generated by the next-generation sequencing technologies (NGS) has great potential in livestock populations. However, a large number of animals are…
Ali Kadhim Yaqoob, Mohamed O. Saeed, Ghufran Khalil Joad, Oliyath Ali
systems Authors: ['Ali Kadhim Yaqoob' 'Mohamed O. Saeed' 'Ghufran Khalil Joad' 'Oliyath Ali'] Increasing the complexity of solving budgetary allocation (NP-hardness problem) has led a wide range of methods to minimize the costs. Metaheuristics and Linear Programming (LP) are the most optimisation in this fields.…
Mengzhen Guo, Stefan Grünewald
We present Lpnet, a variant of the widely used Neighbor-net method that approximates pairwise distances between taxa by a circular phylogenetic network. We first apply standard methods to construct a binary phylogenetic tree and then use integer linear programming to compute an optimal circular orderings that agrees…
Behrooz Bodaghi, Nadezda Sukhorukova
In this paper we propose a new efficient linear programming based approach for multi-resource allocation and location problems in disaster management. Such problems require an integer solution and therefore, in most cases, the computations rely on integer and mixed-integer linear programming solvers. In general, these…
Aihong Ren, Yuping Wang, Xingsi Xue
This paper proposes a new methodology for solving the interval bilevel linear programming problem in which all coefficients of both objective functions and constraints are considered as interval numbers. In order to keep as much uncertainty of the original constraint region as possible, the original problem is first…
A.J.R. Cotter
A simulator, ‘ECOLPS’ in R, is developed and trialed for ecological studies of closed aquatic ecosystems. Its constraint-based approach contrasts with function-based models widely applied in ecology. Total gross production (ΣGP) by ‘wild components’ (= species/life stages, grouped by ecological roles) is maximized…
Authors not listed
Automated chemistry platforms hold the potential to enable large-scale organic synthesis campaigns, such as producing a library of compounds for biological evaluation. The efficiency of such platforms will depend on the schedule according to which the synthesis operations are executed. In this work, we study the…
Zhuo Dai, Yefu Zhou, Bibhas Chandra Giri
In supply chain management, the location of facilities, inventory control, and vehicle routing are three key components. This paper incorporates a two-warehouse inventory system into the location- inventory-routing problems (LIRPs) and develops LIRP models with two warehouses in one-level, two-level, and three-level…
Qianxiang Ai, Joshua Schrier
In a recent paper in this journal (Chem. Mater. 2022, 34, 2545-2552), Twyman et al. studied the environmental stability of crystals by introducing a greedy heuristic algorithm for determining possible oxidation reactions. We show how the problem can be solved exactly, with less code and comparable computational time by…
Hao Hu, Renata Sotirov
We provide several applications of the linearization problem of a binary quadratic problem. We first construct a hierarchy of semidefinite programming relaxations for binary quadratic problems based on the sum-of-squares relaxations and the linearization problem. Then, we propose a new lower bounding strategy, called…
Zixiang Xu
Gene knockout has been used to improve the conversion ratio of strains for some chemical products. Based on mixed integer bi-level linear programming (MIBLP) and cell network models, there have been several algorithms to predict the target for deletion to improve the productivity of chemicals. At present, the cell…
Authors not listed
We present a vector-based method to balance chemical reactions. The algorithm builds candidates in a deterministic way, removes duplicates, and always prints coefficients in the lowest whole-number form. For redox cases, electrons and protons/hydroxide are treated explicitly, so both mass and charge are balanced. We…
Andrew McCluskey
The use of mathematical transformations to reduce non-linear functions to linear problems, which can be tackled with analytical linear regression, is commonplace in the chemistry curriculum. The linearization procedure, however, assumes an incorrect statistical model for real experimental data; leading to biased…
Liwei Cao, Danilo Russo, Vassilios S. Vassiliadis, Alexei Lapkin
A mixed-integer nonlinear programming (MINLP) formulation for symbolic regression was proposed to identify physical models from noisy experimental data. The formulation was tested using numerical models and was found to be more efficient than the previous literature example with respect to the number of predictor…
Tobias Seidel, Lena-Marie Ränger, Thomas Grützner, Michael Bortz
In this work we present a new approach that we use to simulate and optimize multiple dividing wall columns at the same time. Instead of considering all model equations as constraints and all process variables as optimization variables in a large and highly nonlinear optimization problem we only incorporate a subset of…